310 research outputs found
Communication-Efficient Distribution-Free Inference Over Networks
Consider a star network where each local node possesses a set of
distribution-free test statistics that exhibit a symmetric distribution around
zero when their corresponding null hypothesis is true. This paper investigates
statistical inference problems in networks concerning the aggregation of this
general type of statistics and global error rate control under communication
constraints in various scenarios. The study proposes communication-efficient
algorithms that are built on established non-parametric methods, such as the
Wilcoxon and sign tests, as well as modern inference methods such as the
Benjamini-Hochberg (BH) and Barber-Candes (BC) procedures, coupled with
sampling and quantization operations. The proposed methods are evaluated
through extensive simulation studies.Comment: Accepted to the Asilomar Conference on Signals, Systems, and
Computers (2023
Semantic Communications in Networked Systems
We present our vision for a departure from the established way of
architecting and assessing communication networks, by incorporating the
semantics of information for communications and control in networked systems.
We define semantics of information, not as the meaning of the messages, but as
their significance, possibly within a real time constraint, relative to the
purpose of the data exchange. We argue that research efforts must focus on
laying the theoretical foundations of a redesign of the entire process of
information generation, transmission and usage in unison by developing:
advanced semantic metrics for communications and control systems; an optimal
sampling theory combining signal sparsity and semantics, for real-time
prediction, reconstruction and control under communication constraints and
delays; semantic compressed sensing techniques for decision making and
inference directly in the compressed domain; semantic-aware data generation,
channel coding, feedback, multiple and random access schemes that reduce the
volume of data and the energy consumption, increasing the number of supportable
devices.Comment: 9 pages, 6 figures, 1500 word
Minimal data rate stabilization of nonlinear systems over networks with large delays
Control systems over networks with a finite data rate can be conveniently
modeled as hybrid (impulsive) systems. For the class of nonlinear systems in
feedfoward form, we design a hybrid controller which guarantees stability, in
spite of the measurement noise due to the quantization, and of an arbitrarily
large delay which affects the communication channel. The rate at which feedback
packets are transmitted from the sensors to the actuators is shown to be
arbitrarily close to the infimal one.Comment: 16 pages; references have now been adde
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